Actors: a model of concurrent computation in distributed systems
Actors: a model of concurrent computation in distributed systems
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Communications of the ACM
Hybrid neural plausibility networks for news agents
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Using the Booch Method: A Rational Approach
Using the Booch Method: A Rational Approach
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
From Active Objects to Autonomous Agents
IEEE Concurrency
Towards the Abstraction and Generalization of Actor-Based Architectures in Diagnostic Reasoning
Collaboration between Human and Artificial Societies, Coordination and Agent-Based Distributed Computing
EH '99 Proceedings of the 1st NASA/DOD workshop on Evolvable Hardware
A fuzzy evolutionary approach to the classification problem
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
LearnMiner: deductive, tolerant agents for discovering didactic resources on the web
SEKE '02 Proceedings of the 14th international conference on Software engineering and knowledge engineering
Collaborative fuzzy clustering
Pattern Recognition Letters
Info-Miner: Bridging Agent Technology with Approximate Information Retrieval
AFSS '02 Proceedings of the 2002 AFSS International Conference on Fuzzy Systems. Calcutta: Advances in Soft Computing
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We extend the actor-based model of concurrent and distributed programming toward a framework in which the agents can learn emerging behaviours through a fuzzy evolutionary structure. The framework is based on the notion of FuzzyEvoAgent, i.e. an entity that exploiting the basic issues of actors (asynchronous message passing, concurrent computation) is submitted to evolutionary laws that reinforce the most suitable behaviors respecting the environment. The behavior evolution is accomplished without the intervent of external stimulus, so that the actor (an entity that reacts only if it receives a command) may be considered as an adaptive agent. We propose a formal definition as well as an implementation model of FuzzyEvoAgents that has been verified via a simple simulation of Artificial Life.